Iron deficiency in cardiorenal anaemia syndrome in Dodoma, Tanzania

Abstract

Introduction: Iron deficiency (ID) is common in patients with chronic heart failure (CHF). The convergence of CHF, ID, anaemia, and chronic kidney disease (CKD), termed Cardiorenal Anaemia Iron Deficiency Syndrome (CRAIDS), is associated with high morbidity and mortality according to published data from high-income countries. Despite the increasing occurrence of CHF in low- and middle-income countries, such as Tanzania, there is a paucity of published data. This study aims to unmask CRAIDS among CHF patients attending a tertiary hospital in Dodoma, Tanzania.

Method: This descriptive post hoc secondary analysis utilized data from a previous prospective observational study at Benjamin Mkapa Hospital in Dodoma, Tanzania. A total of 268 adult patients with CHF and varying degrees of CKD were included. ID was defined using serum ferritin and transferrin saturation (TSAT) levels. Data were analysed and presented using descriptive and inferential statistical methods. A 2-sided p-value of ≤ 0.05 indicated statistical significance.

Results:  The 268 patients had a mean age of 56.25±14.83 years. There were 154 (57.5%) females. The prevalence of CRAIDS was 32.5% (87/268). Patients with CRAIDS were more likely to have diabetes mellitus (67.8%, p = 0.011), hypertension (62.1%, p = 0.048), New York Association Functional Classification (NYHA) class III/IV (77%, p < 0.001), significant proteinuria (63.2%, p = 0.012), and advanced CKD stages 4/5 (37.9%, p < 0.001). Clinical associations with CRAIDS included diabetes mellitus (AOR 2.10), NYHA III/IV (AOR 2.67), proteinuria (AOR 3.42), and advanced CKD (AOR 5.34).

Conclusion: There is a high burden of CRAIDS among CHF patients in Dodoma, and it is strongly associated with diabetes mellitus, advanced CKD with proteinuria, and poor cardiac function. Early targeted screening and management of ID could improve outcomes in this vulnerable population.

Keywords: cardiorenal anaemia iron deficiency syndrome; chronic heart failure; chronic kidney disease; iron deficiency; Tanzania.

Introduction

Iron is a micronutrient essential for numerous physiological processes, including oxygen transport and cellular metabolism.^[1] The lack of iron is associated with impaired cellular metabolic processes and anaemia. Iron deficiency (ID) is common in individuals with chronic heart failure (CHF) and is an independent indicator of poor cardiovascular outcomes.^[2] Serum ferritin values <100 µg/L indicate absolute ID in CHF, while serum ferritin levels between 100 and 299 µg/L and transferrin saturation (TSAT) <20% are indicative of functional ID.^[3,4] Impaired iron metabolism is reflected in both types, and it is linked to worsening heart failure symptoms, exercise intolerance, and higher hospitalisation and mortality rates.^[1,2] ID affects between 21% and 75% of CHF patients worldwide.^[6-8] In Europe, ID affects 19% of patients as a functional deficiency and 33% of patients as an absolute deficiency, especially in older people with multimorbidities.^{[2, 3, 7]} 

A report from the Netherlands showed an ID of 77.5% of cardiorenal anaemia syndrome (CRAS) patients.^[7] According to Tanzanian data, 49% of CHF patients have ID.^[6] Most research regarding ID in CRAS patients has been done in high-income countries, with little in Tanzania. The term cardiorenal anaemia iron deficiency syndrome (CRAIDS) was coined to highlight the relationship between ID, anaemia, CHF, and CKD and its strong association with high morbidity and mortality rates.^[2,5,7] CRAIDS is defined as a clinical triad of CHF regardless of ejection fraction, CKD with GFR ≤60 mL/min/1.73m², and iron deficiency anaemia with haemoglobin of <12 g/dl for females and <13 g/dl for males with features of iron deficiency based on serum ferritin and TSAT.^[3–6] Improving patients’ outcomes requires an understanding of ID in relation to CRAS in our local setting.^[5] The purpose of this research was to close this information gap and support processes that raise patient survival and care quality.

Method

This descriptive post hoc secondary analysis study was carried out by retrieving data of the previous prospective observational study from the Department of Cardiology at Benjamin Mkapa Hospital in Dodoma, Tanzania.^[9]

A total of 268 patients who met the inclusion criteria were analysed from the previous ethically cleared study. Statistical Package for Social Sciences (SPSS) Windows version 26 program (IBM SPSS, Chicago IL) was used. Descriptive and inferential analyses were performed. 

Categorical data were presented as frequencies and percentages. The Pearson Chi-squared test was used to compare the clinical profiles of patients with and without CRAIDS. To identify factors associated with CRAIDS, both univariate and multivariate logistic regression analyses were performed, yielding Crude Odds Ratios (COR) and Adjusted Odds Ratios (AOR) with 95% confidence intervals (CI). For logistic regression, key assumptions include the absence of high multicollinearity among predictor variables and the linearity of the logit for continuous predictors. A 2-sided p-value of ≤ 0.05 was considered statistically significant.

Results

Prevalence of CRAIDS

Out of the 268 patients, 87 (32.5%) had CRAIDS.

Baseline demographic, clinical, and laboratory parameters of study patients: these are shown in Table 1.

Table 1. Baseline demographic, clinical and laboratory parameters of study patients

Variables	Numbers (%) or Median (IQR)
Age (years) [x ± SD]	56.25 ± 14.83
Sex
Female	154 (57.5)
Male	114 (42.5)
Anthropometrics
Waist circumference, cm	88 (46-118)
Hip circumference, cm	83 (41-109)
Waist-hip ratio (WHR)	1.045 (0.73-2.23)
Blood glucose measurements
Glycated haemoglobin (HBA1C %)	6.0 (4.1-14.6)
Random blood glucose (RBG), mmol/L	6.6 (4.3-23)
Blood pressure measurements (mmHg) Systolic blood pressure (SBP)	133 (98-194)
Diastolic blood pressure (DBP)	76 (59-112)
Baseline median EF, %	49 (10-79)
Iron studies and Red blood indices
Hb, g/dl	12.1 (4.6-16.6)
Mean corpuscular volume (MCV), fl	83 (64-95.7)
Mean corpuscular haemoglobin (MCH), pg	28 (21-32.3)
C-reactive protein (CRP), mg/L	3.6 (0.06-20.4)
Ferritin, µg/L	148 (6.4-2477)
Iron, µmol/L	59 (19-169)
Total iron binding capacity (TIBC), µmol/L	273 (87-413)
Transferrin saturation (TSAT), %	22.4 (5-49.6)
Lipid profile
Triglycerides, mmol/L	5.2 (1.2-9.6)
Low density lipoprotein, mmol/L	3.2 (1.03-7.2)
Total cholesterol, mmol/L	5.3 (2.5-9.6)
Kidney functions
Baseline creatinine, mmol/L	128 (56-351)
Median GFR (mil/min/1.73m2)	47 (15-140)
Median urine protein: creatinine ratio (UPCR), mg/g	35 (0-1300)

Clinical profile of patients based on the presence of CRAIDS

These are shown in Table 2. 

Table 2. Clinical profile of patients based on the presence of CRAIDS

Variables	Total, n (%)	CRAS without ID, n (%)	CRAS with ID  n (%)	p-value
Age groups
< 60	156 (58.2)	109 (60.2)	47 (54)
≥ 60	112 (41.8)	72 (39.8)	40 (46)	0.335
Sex category
Female	154 (57.5)	104 (57.5)	50 (57.5)
Male	114 (42.5)	77 (42.5)	37 (42.5)	0.998
DM status
No	116 (43.3)	88 (48.6)	28 (32.2)
Yes	152 (56.7)	93 (51.4)	59 (67.8)	0.011
HTN Status
No	125 (46.6)	92 (50.8)	33 (37.9)
Yes	143 (53.4)	89 (49.2)	54 (62.1)	0.048
NYHA category
I/II	118 (44)	98 (54.1)	20 (23)
III/IV	150 (56)	83 (45.9)	67 (77)	<0.001
CRP category
< 1.0	44 (16.4)	34 (18.8)	10 (11.5)
≥ 1.0	224 (83.6)	147 (81.2)	77 (88.5)	0.131
EF %
≥ 45	167 (62.3)	116 (64.1)	51 (58.6)
< 45	101 (37.7)	65 (35.9)	36 (41.4)	0.387
UACR, mg/g
Normal	118 (44)	86 (47.5)	32 (36.8)
Increased	150 (56)	95 (52.5)	55 (63.2)	0.012
Advanced CKD staging
≥ 30	221 (82.5)	167 (92.3)	54 (62.1)
< 30	47 (17.5)	14 (7.7)	33 (37.9)	<0.001
Obesity
No	103 (38.4)	69 (38.1)	34 (39.1)
Yes	165 (61.6)	112 (61.9)	53 (60.9)	0.880
Dyslipidemia
No	103 (38.4)	69 (38.1)	34 (39.1)
Yes	165 (61.6)	112 (61.9)	53 (60.9)	0.880

* Pearson Chi-squared test.

Clinical associations with CRAIDS - see Table 3.

In this study, eight potential variables were identified at baseline as clinical associations and were fitted for univariate analysis, with a p-value ≤0.2 considered statistically significant. Thereafter, multivariate analysis and backwards elimination were performed, and the variables were then reduced to four parameters with statistical significance, with a p-value of less than 0.05. Clinical associates were diabetes mellitus: AOR 2.100 (95% CI, 1.141-3.860; p= 0.017); advanced NYHA functional classes III/IV: AOR 2.665 (95% CI, 1.384-5.131; p=003); proteinuria: AOR 3.415 (95% CI, 1.513-7.710, p=0.003) and advanced CKD stages 4/5: AOR 5.341 (95% CI, 2.469-11.553, p <0.001) were associated with CRAIDS.

Table 3. Clinical Associations with CRAIDS

Variables	Total, n (%)	COR (95% CI)	p-value	AOR (95% CI)	p-value
Age groups
< 60	156 (58.2)	Ref		Ref
≥ 60	112 (41.8)	1.288 (0.769-2.159)	0.336	1.373 (0.659-2.858)	0.397
Sex category
Female	154 (57.5)	Ref		Ref
Male	114 (42.5)	0.999 (0.596-1.676)	0.998	1.875 (0.884-3.973)	0.101
DM status
No	116 (43.3)	Ref		Ref
Yes	152 (56.7)	1.994 (1.167-3.408)	0.012	2.100(1.141-3.860)	0.017
HTN Status
No	125 (46.6)	Ref		Ref
Yes	143 (53.4)	1.692 (1.004-2.851)	0.048	1.761 (0.0.969-3.202)	0.063
NYHA category
I/II	44 (16.4)	Ref		Ref
III/IV	165 (83.6)	3.955 (2.218-7.050)	0.001	2.665 (1.384-5.131)	0.003
CRP category
< 1.0	167 (62.3)	Ref		Ref
≥ 1.0	101 (37.7)	1.781 (0.835-3.797)	0.135	1.203 (0.836-3.289)	0.326
UACR, mg/g
Normal	118 (44)	Ref		Ref
Increased	150 (56)	2.810 (1.379-5.724)	0.004	3.415 (1.513-7.710)	0.003
CKD staging
≥ 30	221 (82.5)	Ref		Ref
< 30	47 (17.5)	7.290 (3.633-14.627)	0.001	5.341 (2.469-11.553)	<0.001

*Univariate and multivariate logistic regression.

Discussion

This study aimed to investigate the burden of CRAIDS among patients with CHF in Dodoma, Tanzania. The observed prevalence was 32.5%, which aligns with data from other low- and middle-income countries.^[3,6] A Tanzanian study previously reported iron deficiency (ID) in 49% of CHF patients, while studies from the Netherlands documented even higher ID prevalence up to 77.5% among patients with CRAIDS.^[6,7] These higher figures were largely attributed to the advanced age and presence of multiple comorbidities in the studied populations.^[2,10–12]

Consistent with previous findings, diabetes mellitus, advanced chronic kidney disease (CKD stages 4/5), proteinuria, and poor cardiac functional status (NYHA classes III/IV) emerged as independent clinical associates of CRAIDS. Chronic inflammation and CKD progression were known to impair iron metabolism and erythropoiesis, then appears to underlie these associations.^[2,4] Additionally, the hyperglycaemic state, chronic inflammation, and insulin resistance associated with diabetes mellitus, along with its toxic effects on the heart and kidneys (leading to ischaemic heart disease and diabetic nephrosclerosis), contribute to worsening cardiac and renal functions.^[13,14] Iron plays a vital role in multiple metabolic and physiological processes, including the synthesis of myoglobin, haemoglobin, oxidative and respiratory chain enzymes, and in maintaining the contractile strength of cardiac myocytes. Deficiency in iron may therefore exacerbate the progression of this multimorbid syndrome.^[13,14] Although, this was a single-centre study, it underscores the need for early screening and targeted intervention of ID among CHF patients, especially those with multimorbid syndrome.

Given that, our facility is a national referral hospital that receives patients from peripheral facilities across Tanzania, the findings may have broader relevance within the country and possibly the East African region. Nevertheless, the relatively small and underrepresented sample limits the generalization of the results. A prospective, multi-centre study is warranted to confirm these findings, and an interventional trial would be valuable to assess the effectiveness of proposed screening and management protocols in this context.

Source of funding: None. 

Conflict of interest: None 

References 

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